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Sample GSM4990886

Query DataSets for GSM4990886

Status

Public on Jan 05, 2021

Title

AGO2_Hen1_3

Sample type

SRA

Source name

Drosophila S2 cells

Organism

Drosophila melanogaster

Characteristics

cell line: S2
genotype: hen1
ip target: AGO2
treatment: untreated
rna population: small RNAs

Treatment protocol

generation of cell lines: To generate knockout lines, cells were transfected with either one (for single-gene knockout) or two (for double knockout) cloned versions of pAc-sgRNA-Cas9 (Addgene #49330), constructed as per previously published protocols (Bassett 2014). Starting 3 d after transfection, cells were selected with 5 ug/mL puromycin (Life Technologies). After one week of selection, single cells were sorted into wells to generate clonal lines. After culture for 2–3 weeks, clonal lines were screen for lesions by PCR amplification of the targeted locus followed by TIDE analysis of the amplicon (Brinkman et al. 2014).

Growth protocol

Drosophila S2 cells were grown at 26°C in Schneider’s Drosophila Medium (Life Technologies) supplemented with 10% heat-inactivated FBS (Life Technologies). Cells were passaged 1:5 every 3–5 days.

Extracted molecule

total RNA

Extraction protocol

For immunoprecipitation of FLAG-tagged AGO2, cells were lysed in TBS-N (10 mM Tris, pH 7.5, 150 mM NaCl, 0.5% NP-40, supplemented with protease inhibitors (complete, mini, EDTA-free protease inhibitor tablets, Sigma Aldrich); 500 uL buffer per ~10 million cells) on ice at 4°C for 20 min. Lysate was then clarified by centrifugation at 15000g for 20 min and added to Anti-FLAG M2 Magnetic beads (25 uL per 500 uL of lysate) that had been washed twice with PBST. After rotation at 4°C for 3 h, the beads were washed three times with 200 uL of PBST, and RNA was eluted with Trizol.
Small-RNA libraries were generated as described in the step-by-step protocol available at http://bartellab.wi.mit.edu/protocols.html, with slight modifications. Briefly, between 5–10 g of total RNA was mixed with size-selection markers (18 and 32 nt 5′-radiolabeled RNAs), and for the total-sRNA libraries quantitative sequencing standards were added (0.05 fmol per 1 g total RNA). The samples were first size-selected, before undergoing subtractive hybridization to remove the 2S rRNA (Seitz et al. 2008). Degenerate adaptors (each containing 4 random-sequence nucleotides abutting the ligation junction) were then ligated to the 3′ and 5′ ends of the RNA in the presence of 10% Polyethylene Glycol (PEG 8000, NEB) and 0.5 L of Superasin (Thermo Fisher Scientific) with T4 RNA Ligase 2, truncated K227Q (NEB) and T4 RNA Ligase 1 (NEB), respectively. Reverse transcription was carried out with SuperScript III (NEB), and the cDNA was PCR-amplified using Kapa HiFi HotStart Ready Mix (VWR).

Library strategy

RIP-Seq

Library source

transcriptomic

Library selection

other

Instrument model

Illumina HiSeq 2500

Description

AGO2_miRNA_counts.txt
AGO2_siRNA_counts.csv
AGO2_Hen1_3

Data processing

Small-RNA sequencing reads were processed by trimming the 5′ and 3′ ends using fastx_trimmer (FastX Toolkit; http://hannonlab.cshl.edu/fastx_toolkit/) and cutadapt (Martin 2011), respectively, and then filtering for greater than 99.9% accuracy for all bases using fastq_quality_filter (FastX Toolkit; http://hannonlab.cshl.edu/fastx_toolkit/) with the parameters ‘-q 30 –p 100’.
To call miRNA reads, the first 19 nucleotides of filtered and trimmed reads were string-matched to a dictionary of miRNA sequences. The miRNA dictionary was curated by filtering miRbase_v21 miRNA annotations for all conserved or confidently annotated small RNA species (as annotated by TargetScanFly, release 7.2) as well as their passenger-strand partners. The few species that could not be called unambiguously using only the first 19 nucleotides were collapsed into a single dictionary entry (the sequence of which was chosen randomly to be that of one of the collapsed species), which was listed under a merged name (for example, dme-miR-276a-5p and dme-miR-276b-5p became dme-miR-276ab-5p).
To count reads mapping to siRNA-producing loci, a list of unique, non-overlapping regions in the genome that encompassed all previously published long hairpin loci, all transposons, and all regions of overlapping antisense-transcribed mRNAs (Chung et al. 2008; Czech et al. 2008; Ghildiyal et al. 2008; Kawamura et al. 2008; Okamura et al. 2008; Okamura et al. 2008; Watanabe et al. 2008) was manually curated (Supplemental Table S4). Any regions overlapping with an annotated miRNA transcript were removed from this list. Trimmed and filtered reads from small RNA libraries were then aligned to the genome (UCSC dm6.08 reference assembly) with STAR (V2.4, with the parameters “--alignIntronMax 1 --outFilterMultimapNmax 50 --outFilterMismatchNoverLmax 0.04 --outFilterIntronMotifs RemoveNoncanonicalUnannotated --outSJfilterReads All”). RPKM values for reads mapping to siRNA-generating loci were then enumerated using cufflinks (v2.2.1, with the parameters “--library-type fr-secondstrand --multi-read-correct --max-multiread-fraction 1.0 --no-length-correction --max-bundle-frags 1000000000") (Trapnell et al. 2010) and the curated list of siRNA-producing loci. For the Hen1 samples, siRNA counts were enumerated with the genes.read_group_tracking output file from CuffDiff (v2.2.1, with the parameters “--library-type fr-secondstrand --no-length-correction --multi-read-correct --total-hits-norm --max-bundle-frags 1000000000”).
To count reads mapping to individual siRNAs, a dictionary of highly abundant individual siRNAs was curated by enumerating from the periodate-treated wild-type libraries the top 21 sequences that mapped to an siRNA-generating locus. As with the miRNA analyses, reads corresponding to these individual siRNAs were identified by string-matching the first 19 nucleotides of the filtered and trimmed reads to this dictionary.
For RNAseq data, reads were aligned to the genome, mapped to siRNA-generating loci, and analyzed as described for the small-RNA-seq reads that mapped to siRNA-generating loci but with the command “fr-firststrand” to account for the opposite stranded-ness of the libraries.
Genome_build: dm6
Supplementary_files_format_and_content: All processed .txt files contain non-normalized miRNA counts for the indicated samples
Supplementary_files_format_and_content: All processed .csv files contain RPKM values for either small-RNA sequencing reads or RNA sequencing reads mapping to siRNA-producing loci for the indicated samples with the exception of the Hen1_siRNA_counts.csv file, which contains Cuffdiff estimated counts of reads mapping to siRNA-producing loci in WT and Hen1 cells

Submission date

Dec 28, 2020

Last update date

Apr 06, 2021

Contact name

Elena Kingston

E-mail(s)

[email protected]

Organization name

Whitehead Institute MIT

Street address

Nine Cambridge Center